不同还原过程空燃比大小对降低稀燃汽油机NOx排放的试验研究

运用自行开发设计的稀燃发动机电控系统和催化系统，对稀燃汽油机运用吸附还原催化法在不同的还原过程空燃比条件下降低NOx的排放进行了研究。试验结果表明，还原过程空燃比越小，吸附还原催化器吸附的NOx还原就越彻底，汽油机排出的NOx也越少。但稀燃汽油机的燃油消耗率增加，经济性变差。     

安全气囊气体发生器壳体精密成形方法的研究

论述了安全气囊气体发生器壳体的基本结构形式及其不同的成形方法。提出了流动控制成形力的计算公式、控制腔位置的判断准则及其形状和尺寸的设计方法。通过试验表明，所开发的流动控制成形技术可节约原材料、提高工作效率及产品质喇，具有显著的技术经济效益。     

空气罐控制输液管道水击研究

采用特征线法对瞬时关闭管道终端阀门 ,在安装和不安装空气罐两种状况时 ,管道压力的变化情况进行了数值模拟 ,并分析了空气罐初始容积、空气罐安装位置等参数对管道瞬态水击压力变化的影响 ,结果表明 :在输液管道的适当位置安装容积一定的空气罐能较好地控制水击的产生     

用改进的前向神经网络预测铁路货运量

对影响铁路货运量的因素进行了分析。根据影响铁路货运量的诸因素的特点，介绍了一种改进的前向神经网络预测方法，并建立了铁路货运量前向神经网络预测模型。算例表明，其预测精度高于常规预测方法。     

高速公路可变收费标准模型研究

在介绍可变收费的理论基础上,分析影响高速公路可变收费标准制定的主要因素,并讨论不同时段收费费率同交通量的关系。在设定的可变收费方案下,建立了出行者选择的二元logit模型,根据调研样本,采用最小二乘法对模型参数标定并对设定的可变收费方案进行评价,结果证明可变收费能使交通流在各时段合理分布,从而提高了高速公路的服务水平。     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

Flying with climate liability? Economic valuation of voluntary carbon offsets using forced choices

This study aims to examine how key aspects of voluntary climate action influence economic values of aviation carbon offsets using an Australian case study, where voluntary carbon offset programs for the aviation sector were active under a carbon tax between July 01, 2012 and July 17, 2014. An online survey was administered during the period using choice experiments. This rare and short-lived Australian experience is useful to gain insights into how individuals respond to the new public policy in terms of the perceived economic value of voluntary offsets for air travel. According to the estimation results, supporters of the mandatory tax policy held a welfare value of voluntary carbon offsets for their domestic flights that is three times larger than non-supporters (i.e., $AU27.83 vs. $AU9.40). It is $AU12.27 on average per ton of carbon offsets per person for domestic flights and $AU0.92 for international long-haul flights. The findings endorse that individuals seem to attach personal responsibility for carbon emissions (i.e. climate liability or carbon conscience) to frequent domestic flights, but not so much to intercontinental flights. Furthermore, reported flight frequencies by respondents did not place any significant impact on economic values of voluntary carbon offsets in both domestic and international frameworks. A coupled approach between forced choices and certainty responses was adapted, where no-choice options were retrieved, potentially improving choice experiments. Results suggest that airlines should consider simplifying their carbon offset programs to fixed levels (e.g. £3, £10, and £20 as in the case of British Airways), regardless of geographical boundaries, while governments should promote both mandatory and voluntary climate measures in tandem.     

船舶企业农民工稳定措施研究

分析当前船舶企业用工短缺现象,认为企业应当改变思路,完善机制,充分了解尊重并充分考虑当前农民工的需求,采取稳定农民工的措施。     

An analysis of rail freight operational efficiency and mode share in the British port-hinterland container market

The growth in container shipping poses considerable challenges to efforts to reduce the negative externalities associated with freight transport. There are particular concerns about the impacts of the associated port-hinterland freight flows. Through empirical research, this paper examines trends in the operational efficiency of the British port-hinterland container rail freight market and to assess the impacts of any changes on the overall sustainability of this market. Original survey work conducted in 2007 and 2015 has allowed longitudinal and cross-sectional analysis of the characteristics of this market.The survey findings reveal that rail’s mode share of port container throughput (in TEU) has increased from 14.7% in 2007 to 16.6% in 2015 and it is likely that its share of the associated hinterland activity has also risen. Rail was carrying 25% more TEU by 2015 without an increase in train service provision. Increases in mean train capacity and mean load factor were observed, leading to growth in the mean train load from 44 TEU in 2007 to 55 TEU in 2015. This considerable improvement in operational efficiency is expected to have reduced the negative externalities per unit of transport activity associated with the rail-borne hinterland container flows, though scope is identified for further improvements in sustainability.     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.